Predicting Percolation Threshold Value of EMI SE for Conducting Polymer Composite Systems Through Different Sigmoidal Models

Abstract

Like electrical conductivity, the electromagnetic interference shielding effectiveness (EMI SE) of carbon-containing polymeric composites also goes through a transition phase known as the percolation threshold (PT). In this study, the applicability of various sigmoidal models such as Sigmoidal-Boltzmann (SB), Sigmoidal-Dose Response (SD), Sigmoidal-Hill (SH), Sigmoidal-Logistic (SL), and Sigmoidal-Logistic-1 (SL-1) to determine the PT of EMI SE has been tested for composites of ethylene vinyl acetate (EVA) copolymer and acrylonitrile butadiene rubber (NBR) matrix reinforced with various particulate and fibrous carbon fillers.It is observed that the SB and SD models predicted similar PT. On the other hand, other models reported different values when validated for any particular composite system. The difference in results of PT has been discussed in detail from a viewpoint of the benefits and vice versa of these models. Also, the classical percolation theory has been applied to determine the PT of EMI SE for comparison with the values obtained through the sigmoidal models. In order to judge the universal acceptability of these models, the EMI SE results have been tested for various polymeric composites taken from some published literature. The results indicate that all the models except the SL-1 model can be successfully applied for predicting the PT of EMI SE for polymer composites.

A Methodological Framework for Assessing the Influence of Process Parameters on Strand Stability and Functional Performance in Fused Filament Fabrication

“…Conductive filaments present several complexities associated with their microstructural compositions and manufacturing processes. From an electrical point of view, their conductivity can be described using the percolation theory that defines, in a stochastic manner, the electric behavior accounting for the creation and destruction of conductive paths [35]. Although the possibility of employing FFF to fabricate structures with embedded sensing elements and functional responses has been explored, few studies derived design principles or rules, while several researchers in this field have highlighted the high electrical resistance values and variability in 3D-printed specimens, with the bond formation and quality identified as root causes for high values of resistance and variability [34,36].…”